Prognostic and predictive microRNA panels for heart failure patients with reduced or preserved ejection fraction: a...

Cardiac troponins and natriuretic peptides are benchmark biomarkers for heart failure (HF) with reduced ejection fraction (HFrEF) but have limited prognostic performance for HF patients with preserved ejection fraction (HFpEF). Non-coding RNA-based biomarkers represent an innovative approach to risk-stratify patients and might address the unmet need for minimally invasive prognostic and predictive tools for HF development and HF-related outcomes. Our aim is to investigate the prognostic performance and risk stratification potential of circulating panels of microRNAs (miRNAs) in HFrEF and HFpEF.

A systematic search on PubMed, Web of Science, and Scopus databases was performed for studies reporting miRNAs as prognostic biomarkers in HF patients. A total of 22 studies pooling 5736 participants were included for quantitative analysis. KM-based individual patient data (IPD) analysis was performed in 12 studies (5064 participants).

KM-based IPD analysis in HFrEF allowed the identification of a panel of four miRNAs (miR-27a-3p, miR-129-5p, miR-145-5p, and miR-590-3p) predicting the risk of all-cause death with hazard ratio (HR) 4.26 [2.68-6.76]. MiR-122-5p and miR-423-5p predicted cardiovascular death of HFrEF patients (HR 3.61 [2.67-4.87]). In HFpEF, miR-19a-3p predicted all-cause death of HFpEF patients with HR 2.23 [1.16-4.27]. Moreover, a panel of eight miRNAs (miR-17-5p, miR-20a-5p, miR-21, miR-23, miR-27, miR-106b-5p, miR-210, and miR-221) showed significant association with HF incidence (HR 2.14 [1.81-2.53]).

A comprehensive meta-analysis of KM-based IPD enabled the identification of unique miRNA panels predicting the incidence and severity of HFrEF and HFpEF, supporting the clinical usefulness of miRNA profiling for tailored healthcare and risk stratification in HF patients. Nonetheless, more rigorously designed longitudinal studies are needed to validate the clinical application of miRNAs as prognostic and predictive biomarkers.